Development of a Machine Learning Model Using Multiple, Heterogeneous Data Sources to Estimate Weekly US Suicide Fatalities

Suicide is a leading cause of death in the US. However, official national statistics on suicide rates are delayed by 1 to 2 years, hampering evidence-based public health planning and decision-making. To estimate weekly suicide fatalities in the US in near real time. This cross-sectional national stu...

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Veröffentlicht in:	JAMA network open 2020-12, Vol.3 (12), p.e2030932
Hauptverfasser:	Choi, Daejin, Sumner, Steven A, Holland, Kristin M, Draper, John, Murphy, Sean, Bowen, Daniel A, Zwald, Marissa, Wang, Jing, Law, Royal, Taylor, Jordan, Konjeti, Chaitanya, De Choudhury, Munmun
Format:	Artikel
Sprache:	eng
Schlagworte:	Cross-Sectional Studies Emergency Service, Hospital - statistics & numerical data Estimates Fatalities Forecasting - methods Health Informatics Humans Information Storage and Retrieval Machine Learning Online Only Original Investigation Public health Public Health - statistics & numerical data Public Health Surveillance - methods Real time Suicide - trends Suicide prevention Suicides & suicide attempts Trends United States - epidemiology
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